Overview

Brought to you by YData

Dataset statistics

Number of variables10
Number of observations16,683,936
Missing cells0
Missing cells (%)0.0%
Duplicate rows7,551
Duplicate rows (%)< 0.1%
Total size in memory381.9 MiB
Average record size in memory24.0 B

Variable types

Numeric1
Categorical1
Boolean8

Alerts

Dataset has 7551 (< 0.1%) duplicate rowsDuplicates

Reproduction

Analysis started2025-06-30 09:47:17.975893
Analysis finished2025-06-30 09:49:10.671673
Duration1 minute and 52.7 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

score_threshold
Real number (ℝ)

Distinct17
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean579.6617
Minimum200
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size127.3 MiB
2025-06-30T03:49:10.774208image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum200
5-th percentile200
Q1350
median550
Q3800
95-th percentile1000
Maximum1000
Range800
Interquartile range (IQR)450

Descriptive statistics

Standard deviation243.5397
Coefficient of variation (CV)0.4201411
Kurtosis-1.1871308
Mean579.6617
Median Absolute Deviation (MAD)200
Skewness0.10437537
Sum9.6710386 × 109
Variance59311.587
MonotonicityNot monotonic
2025-06-30T03:49:10.854612image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
250 1112574
 
6.7%
300 1110206
 
6.7%
350 1075235
 
6.4%
200 1067919
 
6.4%
400 1044005
 
6.3%
450 1012852
 
6.1%
600 1009826
 
6.1%
500 1007400
 
6.0%
550 1005980
 
6.0%
650 972930
 
5.8%
Other values (7) 6265009
37.6%
ValueCountFrequency (%)
200 1067919
6.4%
250 1112574
6.7%
300 1110206
6.7%
350 1075235
6.4%
400 1044005
6.3%
450 1012852
6.1%
500 1007400
6.0%
550 1005980
6.0%
600 1009826
6.1%
650 972930
5.8%
ValueCountFrequency (%)
1000 850778
5.1%
950 862768
5.2%
900 874679
5.2%
850 886942
5.3%
800 905544
5.4%
750 925592
5.5%
700 958706
5.7%
650 972930
5.8%
600 1009826
6.1%
550 1005980
6.0%

dice_threshold
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size795.6 MiB
3
4208912 
4
4001366 
2
3822713 
1
2652322 
0
1998623 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters16,683,936
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3 4208912
25.2%
4 4001366
24.0%
2 3822713
22.9%
1 2652322
15.9%
0 1998623
12.0%

Length

2025-06-30T03:49:10.937189image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-06-30T03:49:11.005661image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
3 4208912
25.2%
4 4001366
24.0%
2 3822713
22.9%
1 2652322
15.9%
0 1998623
12.0%

Most occurring characters

ValueCountFrequency (%)
3 4208912
25.2%
4 4001366
24.0%
2 3822713
22.9%
1 2652322
15.9%
0 1998623
12.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 16683936
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3 4208912
25.2%
4 4001366
24.0%
2 3822713
22.9%
1 2652322
15.9%
0 1998623
12.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 16683936
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3 4208912
25.2%
4 4001366
24.0%
2 3822713
22.9%
1 2652322
15.9%
0 1998623
12.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 16683936
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3 4208912
25.2%
4 4001366
24.0%
2 3822713
22.9%
1 2652322
15.9%
0 1998623
12.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
True
11342628 
False
5341308 
ValueCountFrequency (%)
True 11342628
68.0%
False 5341308
32.0%
2025-06-30T03:49:11.059539image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
True
11302706 
False
5381230 
ValueCountFrequency (%)
True 11302706
67.7%
False 5381230
32.3%
2025-06-30T03:49:11.094781image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
False
13159435 
True
3524501 
ValueCountFrequency (%)
False 13159435
78.9%
True 3524501
 
21.1%
2025-06-30T03:49:11.131910image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

smart_five
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
True
11176135 
False
5507801 
ValueCountFrequency (%)
True 11176135
67.0%
False 5507801
33.0%
2025-06-30T03:49:11.169745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

smart_one
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
False
11192076 
True
5491860 
ValueCountFrequency (%)
False 11192076
67.1%
True 5491860
32.9%
2025-06-30T03:49:11.203399image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
True
8405536 
False
8278400 
ValueCountFrequency (%)
True 8405536
50.4%
False 8278400
49.6%
2025-06-30T03:49:11.238965image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
True
9517269 
False
7166667 
ValueCountFrequency (%)
True 9517269
57.0%
False 7166667
43.0%
2025-06-30T03:49:11.274050image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.9 MiB
False
8342532 
True
8341404 
ValueCountFrequency (%)
False 8342532
50.0%
True 8341404
50.0%
2025-06-30T03:49:11.307532image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Interactions

2025-06-30T03:48:45.586076image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-06-30T03:49:11.365856image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
auto_hot_diceconsider_diceconsider_scoredice_thresholdprefer_scorerequire_bothrun_up_scorescore_thresholdsmart_fivesmart_one
auto_hot_dice1.0000.0750.0010.0480.0380.0740.0000.0110.0010.001
consider_dice0.0751.0000.3900.2010.3270.3570.0000.0060.0330.023
consider_score0.0010.3901.0000.0090.2430.3550.0000.0580.0260.021
dice_threshold0.0480.2010.0091.0000.1040.2410.0000.0110.0440.037
prefer_score0.0380.3270.2430.1041.0000.0180.0000.0260.0000.007
require_both0.0740.3570.3550.2410.0181.0000.0000.0710.0130.012
run_up_score0.0000.0000.0000.0000.0000.0001.0000.0000.0000.000
score_threshold0.0110.0060.0580.0110.0260.0710.0001.0000.0090.010
smart_five0.0010.0330.0260.0440.0000.0130.0000.0091.0000.492
smart_one0.0010.0230.0210.0370.0070.0120.0000.0100.4921.000

Missing values

2025-06-30T03:48:45.918386image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-06-30T03:48:52.341295image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

score_thresholddice_thresholdconsider_scoreconsider_dicerequire_bothsmart_fivesmart_oneprefer_scoreauto_hot_dicerun_up_score
09003TrueTrueFalseTrueTrueFalseTrueTrue
19003TrueTrueFalseTrueTrueFalseTrueTrue
29003TrueTrueFalseTrueTrueFalseTrueTrue
39003TrueTrueFalseTrueTrueFalseTrueTrue
49003TrueTrueFalseTrueTrueFalseTrueTrue
59003TrueTrueFalseTrueTrueFalseTrueTrue
69003TrueTrueFalseTrueTrueFalseTrueTrue
79003TrueTrueFalseTrueTrueFalseTrueTrue
89003TrueTrueFalseTrueTrueFalseTrueTrue
99003TrueTrueFalseTrueTrueFalseTrueTrue
score_thresholddice_thresholdconsider_scoreconsider_dicerequire_bothsmart_fivesmart_oneprefer_scoreauto_hot_dicerun_up_score
166839269000FalseTrueFalseTrueFalseFalseFalseTrue
166839274000TrueTrueTrueTrueTrueTrueFalseTrue
166839282500FalseTrueFalseFalseFalseFalseFalseTrue
166839295000TrueTrueTrueTrueFalseTrueTrueTrue
166839307000FalseTrueFalseFalseFalseFalseTrueFalse
166839313500FalseTrueFalseTrueFalseFalseFalseTrue
166839327000FalseTrueFalseTrueFalseFalseFalseFalse
166839338000TrueTrueTrueTrueFalseFalseFalseTrue
166839348500TrueTrueTrueTrueFalseFalseFalseFalse
166839358000TrueTrueTrueTrueFalseTrueTrueTrue

Duplicate rows

Most frequently occurring

score_thresholddice_thresholdconsider_scoreconsider_dicerequire_bothsmart_fivesmart_oneprefer_scoreauto_hot_dicerun_up_score# duplicates
65379003TrueTrueFalseTrueTrueFalseTrueTrue4167
13253004TrueTrueTrueTrueTrueFalseFalseTrue4135
13263004TrueTrueTrueTrueTrueFalseTrueFalse4134
8832504TrueTrueTrueTrueTrueFalseTrueTrue4108
60928503TrueTrueFalseTrueTrueFalseTrueFalse4107
56498003TrueTrueFalseTrueTrueFalseTrueTrue4082
8812504TrueTrueTrueTrueTrueFalseFalseTrue4077
56488003TrueTrueFalseTrueTrueFalseTrueFalse4070
47607003TrueTrueFalseTrueTrueFalseTrueTrue4069
13243004TrueTrueTrueTrueTrueFalseFalseFalse4066